@inproceedings{0125fb4181e84209a1f5e63c03ba353a,
title = "Planematch: patch coplanarity prediction for robust RGB-D reconstruction",
abstract = "We introduce a novel RGB-D patch descriptor designed for detecting coplanar surfaces in SLAM reconstruction. The core of our method is a deep convolutional neural network that takes in RGB, depth, and normal information of a planar patch in an image and outputs a descriptor that can be used to find coplanar patches from other images. We train the network on 10 million triplets of coplanar and non-coplanar patches, and evaluate on a new coplanarity benchmark created from commodity RGB-D scans. Experiments show that our learned descriptor outperforms alternatives extended for this new task by a significant margin. In addition, we demonstrate the benefits of coplanarity matching in a robust RGBD reconstruction formulation. We find that coplanarity constraints detected with our method are sufficient to get reconstruction results comparable to state-of-the-art frameworks on most scenes, but outperform other methods on established benchmarks when combined with traditional keypoint matching.",
keywords = "Co-planarity, Loop closure, RGB-D registration",
author = "Yifei Shi and Kai Xu and Matthias Nie{\ss}ner and Szymon Rusinkiewicz and Thomas Funkhouser",
note = "Funding Information: We are grateful to Min Liu, Zhan Shi, Lintao Zheng, and Maciej Halber for their help on data preprocessing. We also thank Yizhong Zhang for the early discussions. This work was supported in part by the NSF (VEC 1539014/ 1539099, IIS 1421435, CHS 1617236), NSFC (61532003, 61572507, 61622212), Google, Intel, Pixar, Amazon, and Facebook. Yifei Shi was supported by the China Scholarship Council. Funding Information: Acknowledgement. We are grateful to Min Liu, Zhan Shi, Lintao Zheng, and Maciej Halber for their help on data preprocessing. We also thank Yizhong Zhang for the early discussions. This work was supported in part by the NSF (VEC 1539014/ 1539099, IIS 1421435, CHS 1617236), NSFC (61532003, 61572507, 61622212), Google, Intel, Pixar, Amazon, and Facebook. Yifei Shi was supported by the China Scholarship Council. Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2018.; 15th European Conference on Computer Vision, ECCV 2018 ; Conference date: 08-09-2018 Through 14-09-2018",
year = "2018",
doi = "10.1007/978-3-030-01237-3_46",
language = "English (US)",
isbn = "9783030012366",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "767--784",
editor = "Vittorio Ferrari and Cristian Sminchisescu and Yair Weiss and Martial Hebert",
booktitle = "Computer Vision – ECCV 2018 - 15th European Conference, 2018, Proceedings",
address = "Germany",
}